Comparison between the ages for the genders and types

Questions

• What are the differences between the ages for the different combinations of gender and types?
• Do we observe the same changes as globally?

Age effect - General Questions

• What are the differences between the ages?
• Which genes and pathways are differentially expressed between 8w and 52w, between 52w and 104w, between 8w and 104w? Are they the same? Is there a gradient?
• Are they different for the two genders?
• Are they different for the two types?

Loads

Libraries and functions

Warning message in is.na(x[[i]]):
“is.na() applied to non-(list or vector) of type 'environment'”Warning message in rsqlite_fetch(res@ptr, n = n):
“Don't need to call dbFetch() for statements, only for queries”

==========================================================================
*
*  Package WGCNA 1.63 loaded.
*
*    Important note: It appears that your system supports multi-threading,
*    but it is not enabled within WGCNA in R. 
*    To allow multi-threading within WGCNA with all available cores, use 
*
*          allowWGCNAThreads()
*
*    within R. Use disableWGCNAThreads() to disable threading if necessary.
*    Alternatively, set the following environment variable on your system:
*
*          ALLOW_WGCNA_THREADS=<number_of_processors>
*
*    for example 
*
*          ALLOW_WGCNA_THREADS=4
*
*    To set the environment variable in linux bash shell, type 
*
*           export ALLOW_WGCNA_THREADS=4
*
*     before running R. Other operating systems or shells will
*     have a similar command to achieve the same aim.
*
==========================================================================


Allowing multi-threading with up to 4 threads.
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."

Data

Stats

	Wald padj < 0.05	LFC > 0 (Wald padj < 0.05)	LFC < 0 (Wald padj < 0.05)
52w VS 8w (F, SPF)	1799	1038	761
52w VS 8w (F, GF)	1026	635	391
52w VS 8w (M, SPF)	367	246	121
52w VS 8w (M, GF)	230	126	104
104w VS 52w (F, SPF)	216	117	99
104w VS 52w (F, GF)	449	231	218
104w VS 52w (M, SPF)	3428	1845	1583
104w VS 52w (M, GF)	2747	1379	1368
104w VS 8w (F, SPF)	2004	1109	895
104w VS 8w (F, GF)	1428	772	656
104w VS 8w (M, SPF)	3863	2069	1794
104w VS 8w (M, GF)	2340	1195	1145

Differentially expressed genes

  52w VS 8w (F, SPF)    52w VS 8w (F, GF)   52w VS 8w (M, SPF) 
           0.5158421            0.5068226            0.6512262 
   52w VS 8w (M, GF) 104w VS 52w (F, SPF)  104w VS 52w (F, GF) 
           0.7869565            0.6712963            0.6570156 
104w VS 52w (M, SPF)  104w VS 52w (M, GF)  104w VS 8w (F, SPF) 
           0.3856476            0.6308700            0.5813373 
  104w VS 8w (F, GF)  104w VS 8w (M, SPF)   104w VS 8w (M, GF) 
           0.6484594            0.5034947            0.6700855 

Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in stack.default(getgo(rownames(l$deg), "mm10", "geneSymbol")):
“non-vector elements will be ignored”Warning message in stack.default(getgo(rownames(as.data.frame(l$deg)), "mm10", "geneSymbol", :
“non-vector elements will be ignored”

Comparison of the numbers per types

DEG into gene co-expression network

• White: up-regulated
• Black: down-regulated

52w VS 8w

52w VS 8w	M	F
SPF
GF

104w VS 52w

104w VS 52w	M	F
SPF
GF

GO analysis

Biological process

Dot-plot with the most over-represented BP GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

Network based on description similarity

52w VS 8w

52w VS 8w	M	F
SPF
GF

52w VS 8w (M, SPF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/52w_VS_8w_M_SPF.png"

52w VS 8w (F, SPF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/52w_VS_8w_F_SPF.png"

52w VS 8w (M, GF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/52w_VS_8w_M_GF.png"

52w VS 8w (F, GF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/52w_VS_8w_F_GF.png"

104w VS 52w

104w VS 52w	M	F
SPF
GF

104w VS 52w (M, SPF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/104w_VS_52w_M_SPF.png"

104w VS 52w (F, SPF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/104w_VS_52w_F_SPF.png"

104w VS 52w (M, GF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/104w_VS_52w_M_GF.png"

104w VS 52w (F, GF)

GO Tree at "../results/dge/age-effect/age_type_gender/go/104w_VS_52w_F_GF.png"

Cellular components

Dot-plot with the most over-represented CC GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

Molecular functions

Dot-plot with the most over-represented MF GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

KEGG pathways

Error in `$<-.data.frame`(`*tmp*`, labels, value = c("", "", "", "", "", : replacement has 33 rows, data has 54
Traceback:

1. plot_kegg_pathways(age_type_gender_deg$over_represented_KEGG[, 
 .     "category"], age_type_gender_deg$fc_deg, "../results/dge/age-effect/age_type_gender/kegg/over_repr_kegg/")
2. suppressMessages(pathview(gene.data = fc_deg, pathway.id = cat, 
 .     species = "Mus musculus", gene.idtype = "Symbol"))
3. withCallingHandlers(expr, message = function(c) invokeRestart("muffleMessage"))
4. pathview(gene.data = fc_deg, pathway.id = cat, species = "Mus musculus", 
 .     gene.idtype = "Symbol")
5. `$<-`(`*tmp*`, labels, value = c("", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", ""))
6. `$<-.data.frame`(`*tmp*`, labels, value = c("", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", ""))
7. stop(sprintf(ngettext(N, "replacement has %d row, data has %d", 
 .     "replacement has %d rows, data has %d"), N, nrows), domain = NA)

What happen to SPF aging genes in GF?

Genes:

1. Set 52w vs 8w: 52w != 8w (SPF)
2. Set 104w vs 52w: 104w != 52w (SPF)
3. Set all: 52w != 8w (SPF) and 104w != 52w (SPF)

Female

Genes in "../results/dge/age-effect/age_type_gender/spf_f_aging_genes"

deg_52w_vs_8w

1799

deg_104w_vs_52w

216

deg_52w_vs_8w_and_104w_vs_52w

54

No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 1137 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 183 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 1649 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 179 observations”

Male

Genes in "../results/dge/age-effect/age_type_gender/spf_m_aging_genes"

deg_52w_vs_8w

367

deg_104w_vs_52w

3428

deg_52w_vs_8w_and_104w_vs_52w

155

No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 252 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 3341 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 241 observations”No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plot.ly/r/reference/#scatter
Warning message:
“Ignoring 1901 observations”